JavaAlgorithms/DataStructures/Heaps/MinPriorityQueue.java

package DataStructures.Heaps;

/**
 * Minimum Priority Queue It is a part of heap data structure A heap is a specific tree based data
 * structure in which all the nodes of tree are in a specific order. that is the children are
 * arranged in some respect of their parents, can either be greater or less than the parent. This
 * makes it a min priority queue or max priority queue.
 *
 * <p>
 *
 * <p>Functions: insert, delete, peek, isEmpty, print, heapSort, sink
 */
public class MinPriorityQueue {
  private int[] heap;
  private int capacity;
  private int size;

  // calss the constructor and initializes the capacity
  MinPriorityQueue(int c) {
    this.capacity = c;
    this.size = 0;
    this.heap = new int[c + 1];
  }

  // inserts the key at the end and rearranges it
  // so that the binary heap is in appropriate order
  public void insert(int key) {
    if (this.isFull()) return;
    this.heap[this.size + 1] = key;
    int k = this.size + 1;
    while (k > 1) {
      if (this.heap[k] < this.heap[k / 2]) {
        int temp = this.heap[k];
        this.heap[k] = this.heap[k / 2];
        this.heap[k / 2] = temp;
      }
      k = k / 2;
    }
    this.size++;
  }

  // returns the highest priority value
  public int peek() {
    return this.heap[1];
  }

  // returns boolean value whether the heap is empty or not
  public boolean isEmpty() {
    if (0 == this.size) return true;
    return false;
  }

  // returns boolean value whether the heap is full or not
  public boolean isFull() {
    if (this.size == this.capacity) return true;
    return false;
  }

  // prints the heap
  public void print() {
    for (int i = 1; i <= this.capacity; i++) System.out.print(this.heap[i] + " ");
    System.out.println();
  }

  // heap sorting can be done by performing
  // delete function to the number of times of the size of the heap
  // it returns reverse sort because it is a min priority queue
  public void heapSort() {
    for (int i = 1; i < this.capacity; i++) this.delete();
  }

  // this function reorders the heap after every delete function
  private void sink() {
    int k = 1;
    while (2 * k <= this.size || 2 * k + 1 <= this.size) {
      int minIndex;
      if (this.heap[2 * k] >= this.heap[k]) {
        if (2 * k + 1 <= this.size && this.heap[2 * k + 1] >= this.heap[k]) {
          break;
        } else if (2 * k + 1 > this.size) {
          break;
        }
      }
      if (2 * k + 1 > this.size) {
        minIndex = this.heap[2 * k] < this.heap[k] ? 2 * k : k;
      } else {
        if (this.heap[k] > this.heap[2 * k] || this.heap[k] > this.heap[2 * k + 1]) {
          minIndex = this.heap[2 * k] < this.heap[2 * k + 1] ? 2 * k : 2 * k + 1;
        } else {
          minIndex = k;
        }
      }
      int temp = this.heap[k];
      this.heap[k] = this.heap[minIndex];
      this.heap[minIndex] = temp;
      k = minIndex;
    }
  }

  // deletes the highest priority value from the heap
  public int delete() {
    int min = this.heap[1];
    this.heap[1] = this.heap[this.size];
    this.heap[this.size] = min;
    this.size--;
    this.sink();
    return min;
  }

  public static void main(String[] args) {
    // testing
    MinPriorityQueue q = new MinPriorityQueue(8);
    q.insert(5);
    q.insert(2);
    q.insert(4);
    q.insert(1);
    q.insert(7);
    q.insert(6);
    q.insert(3);
    q.insert(8);
    q.print(); // [ 1, 2, 3, 5, 7, 6, 4, 8 ]
    q.heapSort();
    q.print(); // [ 8, 7, 6, 5, 4, 3, 2, 1 ]
  }
}